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A deep learning method for prediction of three-dimensional dose distribution of helical tomotherapy.
Liu, Zhiqiang; Fan, Jiawei; Li, Minghui; Yan, Hui; Hu, Zhihui; Huang, Peng; Tian, Yuan; Miao, Junjie; Dai, Jianrong.
Afiliação
  • Liu Z; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
  • Fan J; Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
  • Li M; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
  • Yan H; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
  • Hu Z; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
  • Huang P; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
  • Tian Y; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
  • Miao J; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
  • Dai J; National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
Med Phys ; 46(5): 1972-1983, 2019 May.
Article em En | MEDLINE | ID: mdl-30870586
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Planejamento da Radioterapia Assistida por Computador / Neoplasias Nasofaríngeas / Aprendizado Profundo Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Med Phys Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China País de publicação: Estados Unidos
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Planejamento da Radioterapia Assistida por Computador / Neoplasias Nasofaríngeas / Aprendizado Profundo Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Med Phys Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China País de publicação: Estados Unidos